Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Crossover Experiments01:16

Crossover Experiments

4.5K
Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in different periods. Crossover experiments are generally used in psychology, the pharmaceutical industry, agriculture, and medicine.
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.
4.5K
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

565
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
565
Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs01:15

Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs

185
Body:Bioequivalence experimental study designs play a pivotal role in testing the effectiveness of various treatments. Key among these are the repeated measures, cross-over, carry-over, and Latin square designs. In the repeated measures design, each subject receives all treatments, allowing for temporal comparisons. This type of design is useful in reducing variability but requires careful planning to avoid bias.The cross-over design, an economical method, involves sequential administration of...
185
The Mantel-Cox Log-Rank Test01:19

The Mantel-Cox Log-Rank Test

1.0K
The Mantel-Cox log-rank test is a widely used statistical method for comparing the survival distributions of two groups. It tests whether a statistically significant difference exists in survival times between the groups without assuming a specific distribution for the survival data, making it a non-parametric test. This flexibility makes the log-rank test particularly valuable in medical research and other fields where the timing of an event, such as death or disease recurrence, is of...
1.0K
Censoring Survival Data01:09

Censoring Survival Data

529
Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
529
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

365
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
365

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Prenatal exposure to prescribed smoke PM<sub>2.5</sub> and low birth weight in Georgia, USA.

Environment international·2026
Same author

The High-resolution Urban Meteorology for Impacts Dataset for Atlanta Metropolitan Region (HUMID-Atlanta).

Scientific data·2026
Same author

Scalable Bayesian Geostatistical Regression Model for Bias-Correcting Large-Scale Daily Satellite-Retrieved Aerosol Optical Depth and Chemical Transport Model Simulations.

Atmospheric environment (Oxford, England : 1994)·2026
Same author

Associations Between Acute Heat Exposure and Hospitalization for Takotsubo Syndrome in the State of California, 2006 to 2019.

Journal of the American Heart Association·2026
Same author

Data fusion in air pollution exposure assessment: Methods, applications, and future directions.

Journal of the Air & Waste Management Association (1995)·2026
Same author

The burden of premature births attributed to heat across 13 countries.

Environment international·2026
Same journal

Instrumental Variable Estimation of Marginal Structural Mean Models for Time-Varying Treatment.

Journal of the American Statistical Association·2026
Same journal

Semiparametric Joint Modeling for Survival Analysis with Longitudinal Covariates.

Journal of the American Statistical Association·2026
Same journal

Dimension Reduction for Large-Scale Federated Data: Statistical Rate and Asymptotic Inference.

Journal of the American Statistical Association·2026
Same journal

Facilitating Heterogeneous Effect Estimation via Statistically Efficient Categorical Modifiers.

Journal of the American Statistical Association·2026
Same journal

Nonparametric Density Estimation of a Long-Term Trend from Repeated Semicontinuous Data.

Journal of the American Statistical Association·2026
Same journal

Functional Integrative Bayesian Analysis of High-dimensional Multiplatform Clinicogenomic Data.

Journal of the American Statistical Association·2026
See all related articles

Related Experiment Video

Updated: Jan 18, 2026

Impact Assessment of Repeated Exposure of Organotypic 3D Bronchial and Nasal Tissue Culture Models to Whole Cigarette Smoke
09:50

Impact Assessment of Repeated Exposure of Organotypic 3D Bronchial and Nasal Tissue Culture Models to Whole Cigarette Smoke

Published on: February 12, 2015

11.5K

Estimating Heterogeneous Exposure Effects in the Case-Crossover Design using BART.

Jacob R Englert1, Stefanie T Ebelt2, Howard H Chang3

  • 1Department of Biostatistics and Bioinformatics, Emory University.

Journal of the American Statistical Association
|September 12, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces Conditional Logistic BART (CL-BART) to identify vulnerable populations exposed to environmental hazards. The method enhances understanding of heat wave impacts on Alzheimer's patients, aiding targeted public health interventions.

Keywords:
Alzheimer’s diseaseBayesian additive regression treesEnvironmental epidemiology

More Related Videos

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.5K
Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR
06:18

Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR

Published on: July 11, 2025

821

Related Experiment Videos

Last Updated: Jan 18, 2026

Impact Assessment of Repeated Exposure of Organotypic 3D Bronchial and Nasal Tissue Culture Models to Whole Cigarette Smoke
09:50

Impact Assessment of Repeated Exposure of Organotypic 3D Bronchial and Nasal Tissue Culture Models to Whole Cigarette Smoke

Published on: February 12, 2015

11.5K
An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.5K
Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR
06:18

Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR

Published on: July 11, 2025

821

Area of Science:

  • Environmental Epidemiology
  • Biostatistics
  • Computational Biology

Background:

  • Epidemiological studies often use matching and conditional likelihood to control confounding in observational research.
  • Nonparametric regression models are increasingly used to estimate individual-level heterogeneous effects, offering detailed exposure-response insights.
  • Identifying subpopulations vulnerable to environmental exposures is a growing public health concern.

Purpose of the Study:

  • To incorporate Bayesian Additive Regression Trees (BART) into conditional logistic regression for case-crossover designs.
  • To develop a novel method, Conditional Logistic BART (CL-BART), for identifying heterogeneous environmental exposure effects.
  • To assess the impact of heat waves on individuals with Alzheimer's disease and identify effect modification by other chronic conditions.

Main Methods:

  • Developed Conditional Logistic BART (CL-BART) using reversible jump Markov chain Monte Carlo.
  • Applied CL-BART to a case-crossover study examining heat wave impacts in California.
  • Utilized variable importance and partial dependence plots to analyze heterogeneous odds ratios.

Main Results:

  • CL-BART successfully identified heterogeneous exposure effects in a case-crossover design.
  • The study demonstrated the impact of heat waves on Alzheimer's disease patients.
  • Effect modification by other chronic conditions was investigated, revealing specific subpopulation vulnerabilities.

Conclusions:

  • CL-BART is an effective tool for identifying vulnerable subpopulations in epidemiological studies.
  • The findings highlight the need for targeted interventions for individuals with Alzheimer's disease during heat waves.
  • The methodology provides strategies for examining heterogeneous odds ratios and understanding complex environmental health interactions.